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Perturbed Runge--Kutta methods (also referred to as downwind Runge--Kutta methods) can guarantee monotonicity preservation under larger step sizes relative to their traditional Runge--Kutta counterparts. In this paper we study, the question…

Numerical Analysis · Mathematics 2018-02-16 Inmaculada Higueras , David I. Ketcheson , Tihamér A. Kocsis

We establish global convergence of the (1+1) evolution strategy, i.e., convergence to a critical point independent of the initial state. More precisely, we show the existence of a critical limit point, using a suitable extension of the…

Neural and Evolutionary Computing · Computer Science 2020-11-20 Tobias Glasmachers

Compact Runge-Kutta (cRK) methods are a class of high order methods for solving hyperbolic conservation laws characterized by their compact stencil including only immediate neighboring finite elements. A Compact Runge-Kutta flux…

Numerical Analysis · Mathematics 2026-04-03 Arpit Babbar , Qifan Chen , Hendrik Ranocha

The efficiency of sampling-based motion planning brings wide application in autonomous mobile robots. The conventional rapidly exploring random tree (RRT) algorithm and its variants have gained significant successes, but there are still…

Robotics · Computer Science 2023-11-02 Ying Zhang , Heyong Wang , Maoliang Yin , Jiankun Wang , Changchun Hua

Many complex problems encountered in both production and daily life can be conceptualized as combinatorial optimization problems (COPs) over graphs. Recent years, reinforcement learning (RL) based models have emerged as a promising…

Machine Learning · Computer Science 2024-04-09 Tianle Pu , Changjun Fan , Mutian Shen , Yizhou Lu , Li Zeng , Zohar Nussinov , Chao Chen , Zhong Liu

We give a detailed analysis of the cost used by the (1+1)-evolutionary algorithm. The problem has been approached in the evolutionary algorithm literature under various views, formulation and degree of rigor. Our asymptotic approximations…

Probability · Mathematics 2014-09-18 Hsien-Kuei Hwang , Alois Panholzer , Nicolas Rolin , Tsung-Hsi Tsai , Wei-Mei Chen

Motion planning problems have been studied by both the robotics and the controls research communities for a long time, and many algorithms have been developed for their solution. Among them, incremental sampling-based motion planning…

Robotics · Computer Science 2012-05-01 Oktay Arslan , Panagiotis Tsiotras

Conic optimization has recently emerged as a powerful tool for designing tractable and guaranteed algorithms for non-convex polynomial optimization problems. On the one hand, tractability is crucial for efficiently solving large-scale…

This paper studies a stochastic optimal control problem with state constraint, where the state equation is described by a controlled stochastic evolution equation with jumps in Hilbert Space and the control domain is assumed to be convex.…

Probability · Mathematics 2017-07-27 Qingxin Meng , Qiuhong Shi , Maoning Tang

Inactive constraints do not contribute to the solution of an optimal control problem, but increase the problem size and burden the numerical computations. We present a novel strategy for handling inactive constraints efficiently by…

Systems and Control · Electrical Eng. & Systems 2021-12-16 Yuanbo Nie , Eric C. Kerrigan

In this study, we investigate the Shallow Water Equations incorporating source terms accounting for Manning friction and a non-flat bottom topology. Our primary focus is on developing and validating numerical schemes that serve a dual…

Numerical Analysis · Mathematics 2023-10-24 Guanlan Huang , Sebastiano Boscarino , Tao Xiong

We introduce a family of stochastic optimization methods based on the Runge-Kutta-Chebyshev (RKC) schemes. The RKC methods are explicit methods originally designed for solving stiff ordinary differential equations by ensuring that their…

Optimization and Control · Mathematics 2022-02-01 Tony Stillfjord , Måns Williamson

We further develop a simple modification of Runge--Kutta methods that guarantees conservation or stability with respect to any inner-product norm. The modified methods can be explicit and retain the accuracy and stability properties of the…

Numerical Analysis · Mathematics 2019-05-27 David I. Ketcheson

By combining Genetic Programming, MAP-Elites and Covariance Matrix Adaptation Evolution Strategy, we demonstrate very high success rates in Symbolic Regression problems. MAP-Elites is used to improve exploration while preserving diversity…

Neural and Evolutionary Computing · Computer Science 2019-06-11 J. -P. Bruneton , L. Cazenille , A. Douin , V. Reverdy

In this paper, exponential Runge-Kutta methods of collocation type (ERKC) which were originally proposed in (Appl Numer Math 53:323-339, 2005) are extended to semilinear parabolic problems with time-dependent delay. Two classes of the ERKC…

Numerical Analysis · Mathematics 2025-12-30 Qiumei Huang , Alexander Ostermann , Gangfan Zhong

The problem of robustly reconstructing a large number from its erroneous remainders with respect to several moduli, namely the robust remaindering problem, may occur in many applications including phase unwrapping, frequency detection from…

Information Theory · Computer Science 2017-04-05 Li Xiao , Xiang-Gen Xia , Haiye Huo

Finite element methods provide accurate and efficient methods for the numerical solution of partial differential equations by means of restricting variational problems to finite-dimensional approximating spaces. However, they do not…

Numerical Analysis · Mathematics 2025-06-24 Robert C. Kirby , John D. Stephens

We consider the energy-optimal control problem for double-integrator systems subject to state and control constraints, with fixed terminal time and free terminal speed. When the constraints become active, the optimal trajectory consists of…

Systems and Control · Electrical Eng. & Systems 2026-04-30 Filippos N. Tzortzoglou , Logan E. Beaver , Andreas A. Malikopoulos

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to…

Machine Learning · Computer Science 2021-06-10 Xinlei Yi , Xiuxian Li , Tao Yang , Lihua Xie , Tianyou Chai , Karl H. Johansson

An explicit numerical strategy that practically preserves invariants is derived for conservative systems by combining an explicit high-order Runge-Kutta (RK) scheme with a simple modification of the standard projection approach, which is…

Numerical Analysis · Mathematics 2020-09-16 Wenjun Cai , Yuezheng Gong , Yushun Wang